ROLE OVERVIEW

Our AI Services and Transformation Unit is seeking a hands-on Technology & Solution Architect who lives at the

intersection of NVIDIA’s AI Factory stack and enterprise client delivery. You are not a generalist — you have personally co-

designed, configured, and validated AI Factory infrastructure using NVIDIA hardware and software. As GSI partner

practitioner, you will work directly with clients and the NVIDIA partner engineering team to architect, co-design, and bring to

production end-to-end AI Factory solutions — from GPU cluster topology and NVIDIA DSX validated designs to Agentic AI

workload onboarding and token economics benchmarking.

WHAT YOU WILL DO

AI Factory Co-Design & Client Advisory

• Lead client-facing AI Factory co-design engagements: assess existing infrastructure, define target AI Factory

architecture using NVIDIA Enterprise AI Factory Validated Design and Enterprise Reference Architectures, and

produce deployment-ready technical blueprints.

• Advise clients on full NVIDIA AI Factory stack selection — compute (HGX B200/GB200/GB300, MGX, NVL72),

networking (InfiniBand NDR/XDR, Spectrum-X), storage, and the NVIDIA AI software layer — matched to their Agentic

AI, Physical AI, or HPC workload profile.

• Apply NVIDIA DSX co-designed reference framework to architect modular, gigawatt-scalable AI Factories; use

Omniverse DSX digital twin blueprints to simulate and validate designs pre-deployment.

• Guide clients on cooling strategy for high-density GPU deployments (40–60+ kW/rack): Direct Liquid Cooling (DLC),

immersion cooling, and RDHx — translating physics into procurement specifications and facility requirements.

NVIDIA GSI Partner Delivery





• Function as unit practitioner-level interface with NVIDIA partner engineering — co-developing client solutions,

navigating the GSI validated design process, and maintaining NVIDIA-Certified System configurations across client

deployments.

• Deploy and configure the NVIDIA AI Enterprise software suite (NIM microservices, NeMo, Nemotron, Dynamo,

RAPIDS, Triton, Run:ai, Mission Control) on client AI Factory infrastructure.

• Execute Agentic AI workload onboarding onto unified AI Factory platforms: implement NVIDIA AI Blueprint for RAG,

configure cuOpt for operational AI, and deploy Kubernetes-native GPU orchestration using Run:ai and NVIDIA

GPU/Network Operators.

• Run GenAI-Perf and MLPerf benchmarks to validate AI Factory delivery quality; present token throughput (tokens/sec,

tokens/watt, tokens/dollar) performance against client SLAs and competitive benchmarks.

Technical Solutioning & Pre-Sales Support

• Support pre-sales on AI Factory pursuits: build detailed BoMs, architecture diagrams, and NVIDIA stack solution

documents for client proposals and RFP responses.

• Quantify business value of AI Factory deployments — translate token economics, GPU utilization rates, and inference

latency improvements into client ROI models.

• Contribute to unit AI Factory IP: delivery accelerators, validated configuration templates, benchmark frameworks, and

reusable reference architecture assets.

QUALIFICATIONS & EXPERIENCE





Experience

• 15+ years in technology consulting or infrastructure engineering; 4+ years specifically in AI Data Center, HPC, or GPU

infrastructure delivery — hands-on build, configuration, and operate/manage is required.• Direct, verifiable experience working within or alongside NVIDIA’s GSI or partner engineering program — this is non-

negotiable.

• Proven track record deploying NVIDIA AI Factory components in production: you have racked, cabled, and configured

DGX/HGX/MGX systems and validated NVIDIA-Certified configurations — not supervised a team that did.

• Experience in client-facing consulting or advisory roles with technical solutioning and proposal ownership.

NVIDIA Technical Stack — Must-Have Depth

Compute

HGX B200/GB200, GB300 NVL72, MGX, DGX SuperPOD, RTX

Networking

InfiniBand NDR/XDR, Spectrum-X, NVLink 4/5, ConnectX-8,

PRO Server

BlueField-3

AI Software

Ops & Orch.

NIM, NeMo, Nemotron, Dynamo, RAPIDS, Triton, NVIDIA AI

Enterprise, CUDA-X

Mission Control, Run:ai, GPU Operator, NGC, Kubernetes, GenAI-

Perf, MLPerf

Build Frameworks

Data & Agents

AI Blueprint for RAG, cuOpt, MIG, Confidential Compute, NVMe-oF

DSX Ref Design, Enterprise AI Factory Validated Design,

Omniverse DSX Digital Twin

storage

• AI Workloads: LLM training/fine-tuning, Agentic AI deployment, inference optimization (FP4/FP8, speculative

decoding), token economics benchmarking.

Education & Certifications

• BS/MS in Computer Science, Computer Architecture, Electrical Engineering, or equivalent applied engineering

background.

• NVIDIA NCP-AI or NCP-DS certification strongly preferred. CDCE or equivalent data center credential is a plus.

📌 Technology & Solution Architect (Jaipur)
🏢 JasApp TechServ
📍 Jaipur